How Cursor AI Slashed Dashboard Migration Time 75%

Salesforce's Mobile Performance Engineering team automated the migration of 20 production monitoring dashboards from Splunk to Tableau using Cursor AI and MCP Server, reducing engineering time by 75%. The migration involved translating 240 queries across dashboards while maintaining 99% production availability. Key technical challenges included converting Splunk's time series aggregation and automatic bucketing to SQL equivalents, mapping dynamic log fields to explicit table schemas, and handling complex date range translations. The team used iterative prompt engineering to teach AI tools to distinguish between syntax conversion and semantic intent, focusing on extracting raw data rather than preserving aggregations. Strategic validation through side-by-side query comparisons and confidence scoring ensured accuracy while preserving productivity gains. The freed engineering capacity enabled the team to shift from reactive migration work to proactive performance engineering, including shift-left AI adoption, preventive dashboards, and distributed tracing implementations.